Synchronization Characterization of DC Microgrid Converter Output Voltage and Improved Adaptive Synchronization Control Methods

This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus voltage oscillation caused by the bifurcation behavior of DC microgrid converters.Firstly,the article elaborately establishes a mathematical model of a single distributed power source with hierarchical control.On this basis,a smallworld network model that can better adapt to the topology structure of DC microgrids is further constructed.Then,a voltage synchronization analysis method based on the main stability function is proposed,and the synchronous characteristics of DC bus voltage are deeply studied by analyzing the size of the minimum non-zero eigenvalue.In view of the situation that the line coupling strength between distributed power sources is insufficient to achieve bus voltage synchronization,this paper innovatively proposes a new improved adaptive controller to effectively control voltage synchronization.And the convergence of the designed controller is strictly proved by using Lyapunov’s stability theorem.Finally,the effectiveness and feasibility of the designed controller in this paper are fully verified through detailed simulation experiments.After comparative analysis with the traditional adaptive controller,it is found that the newly designed controller can make the bus voltages of each distributed power source achieve synchronization more quickly,and is significantly superior to the traditional adaptive controller in terms of anti-interference performance.

A Novel Control Strategy Based onπ-VSG for Inter-Face Converter in Hybrid Microgrid

The rapid development of new energy power generation technology and the transformation of power electronics in the core equipment of source-grid-load drives the power system towards the“double-high”development pattern of“high proportion of renewable energy”and“high proportion of power electronic equipment”.To enhance the transient performance of AC/DC hybrid microgrid(HMG)in the context of“double-high,”aπtype virtual synchronous generator(π-VSG)control strategy is applied to bidirectional interface converter(BIC)to address the issues of lacking inertia and poor disturbance immunity caused by the high penetration rate of power electronic equipment and new energy.Firstly,the virtual synchronous generator mechanical motion equations and virtual capacitance equations are used to introduce the virtual inertia control equations that consider the transient performance of HMG;based on the equations,theπ-type equivalent control model of the BIC is established.Next,the inertia power is actively transferred through the BIC according to the load fluctuation to compensate for the system’s inertia deficit.Secondly,theπ-VSG control utilizes small-signal analysis to investigate howthe fundamental parameters affect the overall stability of the HMG and incorporates power step response curves to reveal the relationship between the control’s virtual parameters and transient performance.Finally,the PSCAD/EMTDC simulation results show that theπ-VSG control effectively improves the immunity of AC frequency and DC voltage in the HMG system under the load fluctuation condition,increases the stability of the HMG system and satisfies the power-sharing control objective between the AC and DC subgrids.

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid

The merits of compressed air energy storage(CAES)include large power generation capacity,long service life,and environmental safety.When a CAES plant is switched to the grid-connected mode and participates in grid regulation,using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage.This occurs because the CAES output voltage does not match the frequency,amplitude,and phase of the power grid voltage.Therefore,an adaptive linear active disturbance-rejection control(A-LADRC)strategy was proposed.Based on the LADRC strategy,which is more accurate than the traditional proportional integral controller,the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters,resulting in improved accuracy and response speed.The problem of large impulse current when CAES is switched to the grid-connected mode is addressed,and the frequency fluctuation is reduced.Finally,the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform.The influence of the k value in the adaptive-adjustment formula on the A-LADRC was analyzed through simulation.The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.

Adaptive VSG control of flywheel energy storage array for frequency support in microgrids

The application of virtual synchronous generator(VSG)control in flywheel energy storage systems(FESS)is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids.Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches,this paper proposes an adaptive VSG control strategy for a flywheel energy storage array(FESA).First,by leveraging the FESA model,a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge(SOC)equalization across units.Furthermore,energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit.The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation.In addition,VSG technology is applied for the grid-connected control of the FESA,and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback.This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation.Subsequently,a parameter design method is developed through a small-signal stability analysis.Consequently,considering the SOC of the FESA,an adaptive control strategy for the inertia damping and the P/ωdroop coefficient of the VSG control is proposed to optimize the grid support services of the FESA.Finally,the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.

Flexible linear clock-based distributed self-triggered active power-sharing secondary control of AC microgrids

Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited computation and communication resources of the secondary controller.To enhance the efficiency of secondary control,we developed a novel distributed self-triggered active power-sharing control strategy by introducing the signum function and a flexible linear clock.Unlike continuous communication–based controllers,the proposed self-triggered distributed controller prompts distributed generators to perform control actions and share information with their neighbors only at specific time instants monitored by the linear clock.Therefore,this approach results in a significant reduction in both the computation and communication requirements.Moreover,this design naturally avoids Zeno behavior.Furthermore,a modified triggering condition was established to achieve further reductions in computation and communication.The simulation results confirmed that the proposed control scheme achieves distributed active power sharing with very few controller triggers,thereby substantially enhancing the efficacy of secondary control in MGs.

Adaptive Predefined-Time Backstepping Control for Grid Connected Photovoltaic Inverter

The system performance of grid-connected photovoltaic(PV)has a serious impact on the grid stability.To improve the control performance and shorten the convergence time,a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic.The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect.To address the“computational explosion problem”in the design process of backstepping control,dynamic surface control is adopted to avoid the analytical calculations of virtual control.The disturbances of the PV system are estimated and compensated by adaptive laws.The control parameters are chosen and the global stability of the closed-loop is ensured by Lyapunov conditions.Simulation results confirm the effectiveness of the proposed controller and ensure the predefined time control in the photovoltaic inverter.

Primary frequency control considering communication delay for grid-connected offshore wind power systems

Offshore wind farms are becoming increasingly distant from onshore centralized control centers,and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control.This causes a deterioration in the performance of the primary frequency control and,in some cases,may even result in frequency instability within the power system.Therefore,a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power.The Padéapproximation was used to model the time delays,and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays.The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored.In addition,a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics.Finally,a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform.The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

Evaluation of Moving Grid Adjustment (MGA) Method in Field Variation Control

Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of spatial variation is needed to ensure unbiased estimation or prediction and thus increase the accuracy of field data evaluation. A moving grid adjustment (MGA) method, which was proposed by Technow, was evaluated through Monte Carlo simulation for its statistical properties regarding field spatial variation control. Our simulation results showed that the MGA method can effectively account for field spatial variation if it does exist;however, this method will not change phenotype results if field spatial variation does not exist. The MGA method was applied to a large-scale cotton field trial data set with two representative agronomic traits: lint yield (strong field spatial pattern) and lint percentage (no field spatial pattern). The results suggested that the MGA method was able to effectively separate the spatial variation including blocking effects from random error variation for lint yield while the adjusted data remained almost identical to the original phenotypic data. With application of the MGA method, the estimated variance for residuals was significantly reduced (62.2% decrease) for lint yield while more genetic variation (29.7% increase) was detected compared to the original data analysis subject to the conventional randomized complete block design analysis. On the other hand, the results were almost identical for lint percentage with and without the application of the MGA method. Therefore, the MGA method can be a useful addition to enhance data analysis when field spatial pattern exists.

Dual-negative-objective Coordinated Control of Brushless Doubly Fed Induction Generator under Unbalanced Grid Voltage

This article proposes a dual-negative-objective coordinated control strategy for brushless doubly fed induction generator(BDFIG)based wind power generation system under unbalanced grid voltage.To alleviate the mechanical stress and impaction on rotating shaft,the negative control objective(NCO)of machine side converter(MSC)is set to suppress the ripple of electromagnetic torque.While the NCO of grid side converter(GSC)is selected to suppress the oscillation of total output active power or the unbalanced degree of total output current for BDFIG generation system.In comparison with traditional single converter control scheme of the MSC or GSC,dual NCOs can be satisfied at the same time due to the enlarged freedom degree in the proposed improved coordinated control system for back-toback converters.The effectiveness of proposed control strategy is validated by simulation and experimental results on a dual-cagerotor BDFIG(DCR-BDFIG)prototype.

Frequency Regulation of Alternating Current Microgrid Based on Hierarchical Control Using Fuzzy Logic

An alternating current(AC)microgrid is a system that integrates renewable power,power converters,controllers and loads.Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse of the system.The existing frequency control methods use traditional proportion integration(PI)controllers,which cannot adjust PI parameters in real-time to respond to the status changes of the system.Hierarchical control driven by fuzzy logic allows real-time adjustment of the PI parameters and the method used a two-layer control structure.The primary control used droop control to adjust power distribution,and fuzzy logic was used in the voltage loop of the primary control.The secondary control was added to make up for frequency deviation caused by droop control,and fuzzy logic was used in the secondary frequency control to deal with the dynamic change of frequency caused by the disturbances of loads.The proposed method was simulated in Matlab/Simulink.In the primary control,the proposed method reduced the total harmonic distortion(THD)of two cycles of the output voltage from 4.19%to 3.89%;in the secondary control,the proposed method reduced the frequency fluctuation of the system by about 0.03 Hz and 0.04 Hz when the load was increased and decreased,respectively.The results show that the proposed methods have a better effect on frequency maintenance and voltage control of the AC microgrid.

Gradient Recovery Based Two-Grid Finite Element Method for Parabolic Integro-Differential Optimal Control Problems

In this paper, the optimal control problem of parabolic integro-differential equations is solved by gradient recovery based two-grid finite element method. Piecewise linear functions are used to approximate state and co-state variables, and piecewise constant function is used to approximate control variables. Generally, the optimal conditions for the problem are solved iteratively until the control variable reaches error tolerance. In order to calculate all the variables individually and parallelly, we introduce a gradient recovery based two-grid method. First, we solve the small scaled optimal control problem on coarse grids. Next, we use the gradient recovery technique to recover the gradients of state and co-state variables. Finally, using the recovered variables, we solve the large scaled optimal control problem for all variables independently. Moreover, we estimate priori error for the proposed scheme, and use an example to validate the theoretical results.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Exponential stabilization of linear systems with feedback optimization and its application to microgrids control

This paper proposes a feedback-optimization-based control method for linear time-invariant systems,which is aimed to exponentially stabilize the system and,meanwhile,drive the system output to an approximate solution of an optimization problem with convex set constraints and affine inequality constraints.To ensure the exponential stability of the closed-loop system,the original optimization problem is first reformulated into a counterpart that has only convex set constraints.It is shown that the optimal solution of the new optimization problem is an approximate optimal solution of the original problem.Then,based on this new optimization problem,the projected primal–dual gradient dynamics algorithm is used to design the controller.By using the singular perturbation method,sufficient conditions are provided to ensure the exponential stability of the closed-loop system.The proposed method is also applied to microgrid control.

Adaptive Droop Control for Circulating Current Suppression in Microgrid Based on Fuzzy Logic

Circulating currents in a microgrid increase the power loss of the microgrid, reduce the operational efficiency, as well as affect the power quality of the microgrid. The existing literature is seldom concerned with methods to suppress the loop currents using fuzzy logic control. In this paper, a method based on fuzzy control of droop coefficients is proposed to suppress the circulating currents inside the microgrid.The method combines fuzzy control with droop control and can achieve the effect of suppressing the circulating currents by adaptively adjusting the droop coefficients to make the power distribution between each subgrid more balanced. To verify the proposed method, simulation is carried out in Matlab/Simulink environment, and the simulation results show that the proposed method is significantly better than the traditional proportional-integral control method. The circulating currents reduce from about 10 A to several nanoamperes, the bus voltage and frequency drops are significantly improved, and the total harmonic distortion rate of the output voltage reduces from 4.66% to 1.06%. In addition, the method used in this paper can be extended to be applied in multiple inverters connected in parallel, and the simulation results show that the method has a good effect on the suppression of circulating currents among multiple inverters.

Analysis and synchronization controller design of dual-port gridforming voltage-source converters for different operation modes

Grid-tie voltage source converters(VSCs)can operate in three distinct modes:AC-dominant,DC-dominant,and balanced,depending on the placement of the stiff voltage sources.The distinct operation modes of the VSCs traditionally demand different synchronization control techniques,leading to heterogeneous VSCs.It is challenging for the power system to accommodate and coordinate heterogeneous VSCs.A promising universal synchronization control technique for VSCs is the DC-link voltage synchronization control(DVSC)based on a lead compensator(LC).The LC DVSC stabilizes both the DC and AC voltages of a VSC while achieving synchronization with the AC grid.This results in a dual-port grid-forming(DGFM)characteristic for the VSC.However,there has been very limited study on the stability and synchronization controller design of the VSCs with the LC DVSC operating in various modes.To bridge this gap,the paper presents a quantitative analysis on the stability and steady-state performance of the LC DVSC in all three operation modes of the DGFM VSC.Based on the analysis,the paper provides step-by-step design guidelines for the LC DVSC.Furthermore,the paper uncovers an instability issue related to the LC DVSC when the DGFM VSC operates in the balanced mode.To tackle the instability issue,a virtual resistance control is proposed and integrated with the LC DVSC.Simulation results validate the analysis and demonstrate the effectiveness of the DGFM VSC with the LC DVSC designed using the proposed guidelines in all three operation modes.Overall,the paper demonstrates the feasibility of employing the DGFM VSC with the LC DVSC for all three possible operation modes,which can help overcome the challenges associated with accommodating and coordinating heterogeneous VSCs in the power system.

Regional Multi-Agent Cooperative Reinforcement Learning for City-Level Traffic Grid Signal Control

This article studies the effective traffic signal control problem of multiple intersections in a city-level traffic system.A novel regional multi-agent cooperative reinforcement learning algorithm called RegionSTLight is proposed to improve the traffic efficiency.Firstly a regional multi-agent Q-learning framework is proposed,which can equivalently decompose the global Q value of the traffic system into the local values of several regions Based on the framework and the idea of human-machine cooperation,a dynamic zoning method is designed to divide the traffic network into several strong-coupled regions according to realtime traffic flow densities.In order to achieve better cooperation inside each region,a lightweight spatio-temporal fusion feature extraction network is designed.The experiments in synthetic real-world and city-level scenarios show that the proposed RegionS TLight converges more quickly,is more stable,and obtains better asymptotic performance compared to state-of-theart models.

Heuristic-Based Optimal Load Frequency Control with Offsite Backup Controllers in Interconnected Microgrids

The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures.The study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input parameters.Also,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the models.The models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat rate.Model validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the SBS.Results show that these models accurately predict SBS,with LGBM providing outstanding performance.SHAP(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on SBS.Consequently,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.